NVIDIA-Certified Professional
NVIDIA AI Operations Certification Exam
(NCP-AIO)
What is the NVIDIA AI Operations Certification (NCP-AIO)?
The NCP-AI Operations certification is an intermediate-level credential that validates a candidate’s ability to monitor, troubleshoot, and optimize AI infrastructure by NVIDIA. The exam is online and proctored remotely, includes 30 multiple choice questions, 3 hands-on lab exercises, and has a 120-minute time limit.
Note: The hands-on lab is completed as part of the 120-minute exam session. Once the exam begins, the lab environment is automatically provisioned, and you must complete both the multiple-choice section and the hands-on lab within the allotted time.
To successfully complete the lab, you should be comfortable using a Linux command-line interface operating on live clusters using Slurm, Kubernetes, and Base Command Manager.
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Who is AI Operations Certification for?
The NVIDIA-Certified Professional: AI Operations exam is for professionals who manage and maintain AI infrastructure in data centers. It is especially relevant to those who administer AI clusters, schedule workloads, and troubleshoot performance issues using tools such as Slurm, Kubernetes, and NVIDIA Base Command Manager..
What are the Key Responsibilities of AI Operations Professionals?
- AI Compute Management:
Maintain GPU-based compute platforms, drivers, software, and containers. - Cluster and Workload Management: Administer clusters, provision resources, and schedule AI workloads using tools such as Slurm, Kubernetes, and Run.
- Networking and Storage: Configure networking for AI workloads and manage storage for performance and capacity.
- Monitoring and Optimization: Monitor cluster health and resource utilization to keep AI workloads running efficiently.
- Troubleshooting: Diagnose and resolve issues with containers, cluster management, networking components, and storage performance.
What are the Recommended Qualifications for AI Operations Professionals Who Want to Take This Exam?
- Experience: 2–3 years of hands-on experience managing AI infrastructure in a data center.
- Infrastructure Fundamentals: Understanding of AI compute, networking, storage, and data center operations. .
- AI Infrastructure Technologies: Expertise in NVIDIA GPUs, DPUs, and AI software stacks, including drivers and containers.
- Data Center Operations: Experience monitoring cluster health, managing resources, and maintaining AI compute platforms.
- Workload Management: Familiarity with Slurm, Kubernetes, and NVIDIA Base Command Manager for cluster administration and workload scheduling.
- Troubleshooting: Ability to diagnose cluster issues, run a Kubernetes workload, and add a node to a cluster using Base Command Manager.
Exam Structure
This exam has two sections: a multiple-choice section and a performance-based test section (or hands-on lab). Each section is worth 50% of the overall score. The score of the two sections is combined for a total score resulting in a pass or fail. You will receive a score report indicating how you performed on each topic, and each section.
The performance-based test section includes three challenges. A short scenario describes a common problem for you to solve. You will be in a live virtual machine with an instruction panel providing you with the scenario and any resources you may need. To complete the performance-based test you will need to be comfortable using Slurm in BCM to troubleshoot a cluster, using Kubernetes to run a workload, and using BCM to add a node to a cluster.
Certification Learning Path
NCP-AIO Exam Preparation Topics, Recommended Training and Reading
The information below is intended to help you prepare for this exam.
Topics covered, weight per topic, recommended training, and additional readings are provided.
Practice Questions
Explore sample questions to get familiar with the topics and question styles you may encounter on the certification exam.
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